Content‐based citation analysis: The next generation of citation analysis
Abstract
Traditional citation analysis has been widely applied to detect patterns of scientific collaboration, map the landscapes of scholarly disciplines, assess the impact of research outputs, and observe knowledge transfer across domains. It is, however, limited, as it assumes all citations are of similar value and weights each equally. Content‐based citation analysis ( CCA ) addresses a citation's value by interpreting each one based on its context at both the syntactic and semantic levels. This paper provides a comprehensive overview of CAA research in terms of its theoretical foundations, methodical approaches, and example applications. In addition, we highlight how increased computational capabilities and publicly available full‐text resources have opened this area of research to vast possibilities, which enable deeper citation analysis, more accurate citation prediction, and increased knowledge discovery.
Cite this
Ying Ding, Guo Freeman, Tamy Chambers, Min Song, Xiaolong Wang, ChengXiang Zhai (2014). Content‐based citation analysis: The next generation of citation analysis. Journal of the Association for Information Science and Technology. https://doi.org/10.1002/asi.23256
@article{ying2014contentbased,
title = {Content‐based citation analysis: The next generation of citation analysis},
author = {Ding, Ying and Freeman, Guo and Chambers, Tamy and Song, Min and Wang, Xiaolong and Zhai, ChengXiang},
year = {2014},
journal = {Journal of the Association for Information Science and Technology},
doi = {10.1002/asi.23256}
}Citations in this library
Stored only when both papers are in the corpus — 251 citations exist upstream.